Genetic-algorithm-based layout optimization of an offshore wind farm under real seabed terrain encountering an engineering cost model

Abstract

Optimizing the layout of an offshore wind farm can increase its total energy output. However, previous studies did not consider the seabed terrain, which can affect the lengths of the turbine supporting structures and thus affect the cost of electricity (COE) of the wind farm. At present, it is not clear whether layouts that have been optimized without considering the terrain can be applied under real terrains. Consequently, this study used genetic algorithm to innovatively optimize the offshore wind farm layouts under different seabed terrains, including a real one at Nanao Island. Moreover, an engineering cost model was developed and employed to predict the initial capital costs of the wind farms. A Gaussian-based wake model was used to predict the wind fields at these wind farms. For complex terrains, when the layouts that were optimized without considering the terrain were applied, the COEs of the wind farms increased by 27.3%. For flattened terrains, they only increased by 3.8%. Thus, layout optimizations that consider the terrain are necessary for real applications. Besides, the COEs of wind farms had almost no sensitivity to the terrain if they had the same mean water depth, with a maximum difference of 4.79% between various terrains.